Development and Validation of a Random Forest Risk Prediction Pneumothorax Model in Percutaneous Transthoracic Needle Biopsy

10 December 2021 : Clinical Research

Hong Lin Wu^1ABCDEF, Gao Wu Yan^2ADF, Li Cheng Lei^3BC, Yong Du^4AD, Xiang Ke Niu^1DF, Tao Peng^1FG*

DOI: 10.12659/MSM.932137

Med Sci Monit 2021; 27:e932137

Background Material and Methods Results Discussion Conclusions References

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Table 3 Prediction performance of models based on 15 risk factors.

Models	Development set				Verification set
Models	LR	SVM	DT	RF	LR	SVM	DT	RF
Sensitivity	0.701	0.781	0.759	0.825	0.581	0.791	0.884	0.930
Specificity	0.500	0.574	0.676	0.806	0.667	0.611	0.556	0.759
Accuracy	0.612	0.690	0.722	0.816	0.629	0.691	0.701	0.835
PPV	0.640	0.699	0.748	0.843	0.581	0.618	0.613	0.755
NPV	0.568	0.674	0.689	0.784	0.667	0.786	0.857	0.932
PPV – positive predictive value; NPV – negative predictive value; LR – logistic regression; SVM – support vector machine; DT – decision tree; RF – random forest.

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